Hi,
one thing which I find irritating is the behaviour of
the modulo operation for arrays:
Compare:
In [1]: from scipy import *
In [2]: -0.4 % 1.0
Out[2]: 0.59999999999999998
In [3]: x=arange(-0.6,1.0,0.1)
In [4]: x%1.0
Out[4]:
array([ -6.00000000e-01, -5.00000000e-01, -4.00000000e-01,
-3.00000000e-01, -2.00000000e-01, -1.00000000e-01,
1.11022302e-16, 1.00000000e-01, 2.00000000e-01,
3.00000000e-01, 4.00000000e-01, 5.00000000e-01,
6.00000000e-01, 7.00000000e-01, 8.00000000e-01,
9.00000000e-01])
Even worse (IMHO): take a scalar (I know it is still an array,
but it does not look like one ;-) from the array
In [5]: x[2]
Out[5]: -0.39999999999999997
In [6]: x[2] % 1.0
Out[6]: -0.39999999999999997
It seems that for arrays % behaves like `fmod` and not like `mod`.
I find this confusing as it is in contrast to the
python 2.4 documentation:
"5.6. Binary arithmetic operations"
"""The % (modulo) operator yields the remainder from the division
of the first argument by the second. [...]
The arguments may be floating point numbers, e.g.,
3.14%0.7 equals 0.34 (since 3.14 equals 4*0.7 + 0.34.)
The modulo operator always yields a result with the same sign as
its second operand (or zero); the absolute value of the result
is strictly smaller than the absolute value of the second
operand."""
Would it be possible for the new scipy core that % behaves
the same (standard python) way for scalars and for arrays?
Best,
Arnd